Adaptive Detached Eddy Simulation and Passive Scalar Transport Modeling for Hybrid RANS/LES

The work described in this dissertation, follows the attempt made in Reddy et al. (2014a), to make Detached Eddy Simulation model more like traditional LES in eddy simulation region. Work done by Reddy et al. (2014a) proposed the l^2w DDES model that shares a similar formulation with Smagorinsky model in eddy simulation region. In the present research, an adaptive procedure was devised (Yin et al., 2015), to allow automatic adjustment of a model coefficient CDES to flow condition and grid resolution. The adaptive method is based on the Germano identity, and on a lower limiting value that is a function of the grid resolution and the Kolmogoroff length scale. The function, being a gauge for grid resolution, allows the model coefficient to be computed dynamically, wherever suitable. To extend adaptive DES to compressible flow and heat transfer, a passive scalar transport model is proposed for Hybrid RANS/LES (Yin and Durbin, 2016b). This too is an adaptive model. Adaptivity is based on computing test-filter fluxes. The formulation proves to be especially effective on coarse grids, as occur in DES. Under the principle that DES should converge to wall-resolved LES as the mesh becomes fine near the wall, a modification is made on the adaptive DES model to make this limit feasible (Yin and Durbin, 2016a). The modification is to the limiting function. It is found that the RANS region shrinks to y+ ∼ 5 on fine meshes, thus allowing the model to be almost equivalent to wall-resolved LES. One place where the wall-resolved asymptote can play a role is in laminar to turbulent transition. Both the original and modified formulation are tested in orderly, bypass, and separation induced transition. Three separated test cases are also included here: a series of 3-D diffusers, jet in cross flow, and rotating channel flows | for more elaborate testing of proposed model. The 3-D diffuser series, reveals that the adaptive method in Yin et al. (2015) has discrepancies with LES even on fine meshes, which partially motivates the revised model (Yin and Durbin, 2016a). The JICF test case validated both the passive scalar transport model in Yin and Durbin (2016b) and the revised model in Yin and Durbin (2016a). And rotating channel flow gives a more detailed assessment of the revised model. In summary, adaptive DES and passive scalar transport models are proposed. They adapt to flow and geometry. The passive scalar transport model is compatible with both wall-resolved LES and hybrid RANS/LES models

High-Efficiency Transduction of Primary Human Hematopoietic Stem/Progenitor Cells by AAV6 Vectors: Strategies for Overcoming Donor-Variation and Implications in Genome Editing.

We have reported that of the 10 commonly used AAV serotype vectors, AAV6 is the most efficient in transducing primary human hematopoietic stem/progenitor cells (HSPCs). However, the transduction efficiency of the wild-type (WT) AAV6 vector varies greatly in HSPCs from different donors. Here we report two distinct strategies to further increase the transduction efficiency in HSPCs from donors that are transduced less efficiently with the WT AAV6 vectors. The first strategy involved modifications of the viral capsid proteins where specific surface-exposed tyrosine (Y) and threonine (T) residues were mutagenized to generate a triple-mutant (Y705 + Y731F + T492V) AAV6 vector. The second strategy involved the use of ex vivo transduction at high cell density. The combined use of these strategies resulted in transduction efficiency exceeding ~90% in HSPCs at significantly reduced vector doses. Our studies have significant implications in the optimal use of capsid-optimized AAV6 vectors in genome editing in HSPCs

Reduced MLH3 Expression in the Syndrome of Gan-Shen Yin Deficiency in Patients with Different Diseases

Traditional Chinese medicine formulates treatment according to body constitution (BC) differentiation. Different constitutions have specific metabolic characteristics and different susceptibility to certain diseases. This study aimed to assess the characteristic genes of gan-shen Yin deficiency constitution in different diseases. Fifty primary liver cancer (PLC) patients, 94 hypertension (HBP) patients, and 100 diabetes mellitus (DM) patients were enrolled and classified into gan-shen Yin deficiency group and non-gan-shen Yin deficiency group according to the body constitution questionnaire to assess the clinical manifestation of patients. The mRNA expressions of 17 genes in PLC patients with gan-shen Yin deficiency were different from those without gan-shen Yin deficiency. However, considering all patients with PLC, HBP, and DM, only MLH3 was significantly lower in gan-shen Yin deficiency group than that in non-gen-shen Yin deficiency. By ROC analysis, the relationship between MLH3 and gan-shen Yin deficiency constitution was confirmed. Treatment of MLH3 (−/− and −/+) mice with Liuweidihuang wan, classical prescriptions for Yin deficiency, partly ameliorates the body constitution of Yin deficiency in MLH3 (−/+) mice, but not in MLH3 (−/−) mice. MLH3 might be one of material bases of gan-shen Yin deficiency constitution

Development of the ℓ² ω Delayed Detached Eddy Simulation model with dynamically computed constant

The current work puts forth an implementation of a dynamic procedure to locally compute the value of the model constant CDES , as used in the eddy simulation branch of Delayed Detached Eddy Simulation (DDES). Former DDES formulations [P. R. Spalart et al., "A new version of detached-eddy simulation, resistant to ambiguous grid densities," Theor. Comput. Fluid Dyn. 20, 181 (2006); M. S. Gritskevich et al., "Development of DDES and IDDES formulations for the k omega shear stress transport model," Flow, Turbul. Combust. 88, 431 (2012)] are not conducive to the implementation of a dynamic procedure due to uncertainty as to what form the eddy viscosity expression takes in the eddy simulation branch. However, a recent, alternate formulation [K. R. Reddy et al., "A DDES model with a Smagorinsky-type eddy viscosity formulation and log-layer mismatch correction," Int. J. Heat Fluid Flow 50, 103 (2014)] casts the eddy viscosity in a form that is similar to the Smagorinsky, LES (Large Eddy Simulation) sub-grid viscosity. The resemblance to the Smagorinsky model allows the implementation of a dynamic procedure similar to that of Lilly [D. K. Lilly, "A proposed modification of the Germano subgrid-scale closure method," Phys. Fluids A 4, 633 (1992)]. A limiting function is proposed which constrains the computed value of CDES , depending on the fineness of the grid and on the computed solution. In addition to the dynamic procedure, influence of inflow condition is also explored in this work.</p

Adaptive Detached Eddy Simulation and Passive Scalar Transport Modeling for Hybrid RANS/LES

The work described in this dissertation, follows the attempt made in Reddy et al. (2014a), to make Detached Eddy Simulation model more like traditional LES in eddy simulation region. Work done by Reddy et al. (2014a) proposed the l^2w DDES model that shares a similar formulation with Smagorinsky model in eddy simulation region. In the present research, an adaptive procedure was devised (Yin et al., 2015), to allow automatic adjustment of a model coefficient CDES to flow condition and grid resolution. The adaptive method is based on the Germano identity, and on a lower limiting value that is a function of the grid resolution and the Kolmogoroff length scale. The function, being a gauge for grid resolution, allows the model coefficient to be computed dynamically, wherever suitable. To extend adaptive DES to compressible flow and heat transfer, a passive scalar transport model is proposed for Hybrid RANS/LES (Yin and Durbin, 2016b). This too is an adaptive model. Adaptivity is based on computing test-filter fluxes. The formulation proves to be especially effective on coarse grids, as occur in DES. Under the principle that DES should converge to wall-resolved LES as the mesh becomes fine near the wall, a modification is made on the adaptive DES model to make this limit feasible (Yin and Durbin, 2016a). The modification is to the limiting function. It is found that the RANS region shrinks to y+ ∼ 5 on fine meshes, thus allowing the model to be almost equivalent to wall-resolved LES. One place where the wall-resolved asymptote can play a role is in laminar to turbulent transition. Both the original and modified formulation are tested in orderly, bypass, and separation induced transition. Three separated test cases are also included here: a series of 3-D diffusers, jet in cross flow, and rotating channel flows | for more elaborate testing of proposed model. The 3-D diffuser series, reveals that the adaptive method in Yin et al. (2015) has discrepancies with LES even on fine meshes, which partially motivates the revised model (Yin and Durbin, 2016a). The JICF test case validated both the passive scalar transport model in Yin and Durbin (2016b) and the revised model in Yin and Durbin (2016a). And rotating channel flow gives a more detailed assessment of the revised model. In summary, adaptive DES and passive scalar transport models are proposed. They adapt to flow and geometry. The passive scalar transport model is compatible with both wall-resolved LES and hybrid RANS/LES models.</p

Passive Scalar Transport Modeling for Hybrid RANS/LES Simulation

A transport model for hybrid RANS/LES simulation of passive scalars is proposed. It invokes a dynamically computed subgrid Prandtl number. The method is based on computing test-filter fluxes. The formulation proves to be especially effective on coarse grids, as occur in DES. After testing it in a wall resolved LES, the present formulation is applied to the Adaptive DDES model of Yin et al. (Phys. Fluids 27, 025105 2015). It is validated by turbulent channel flow and turbulent boundary layer computations.This is the peer-reviewed version of the following article: Yin, Zifei, and Paul A. Durbin. "Passive Scalar Transport Modeling for Hybrid RANS/LES Simulation." Flow, Turbulence and Combustion 98, no. 1 (2017): 177-194, which has been published in final form at DOI: 10.1007/s10494-016-9746-1. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Self-Archiving. Posted with permission.</p